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Irfanuruchi/Qwen3-4B-Computer-Science-GGUF overview

Qwen3 4B Computer Science GGUF GGUF release of Qwen3 4B Computer Science , a specialized language model fine tuned for computer science, software engineering, …

ggufllama.cpptext-generationconversationalcodeprogrammingcomputer-scienceqwen3base_model:Qwen/Qwen3-4Bbase_model:quantized:Qwen/Qwen3-4Blicense:apache-2.0endpoints_compatibleregion:us

Runs locally from ~2.33 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation

Repository Files & Downloads

5 GGUF files detected
Direct downloads for local inference
FileTypeQuantizationSizeLink
Qwen3-4B-Computer-Science-BF16.ggufGGUFBF167.50 GBDownload
Qwen3-4B-Computer-Science-Q4_K_M.ggufGGUFQ4_K_M2.33 GBDownload
Qwen3-4B-Computer-Science-Q5_K_M.ggufGGUFQ5_K_M2.69 GBDownload
Qwen3-4B-Computer-Science-Q6_K.ggufGGUFQ6_K3.08 GBDownload
Qwen3-4B-Computer-Science-Q8_0.ggufGGUFQ8_03.99 GBDownload

Model Details

Model IDIrfanuruchi/Qwen3-4B-Computer-Science-GGUF
AuthorIrfanuruchi
Pipelinetext-generation
Licenseapache-2.0
Base modelQwen/Qwen3-4B
Last modified2026-07-24T10:58:31.000Z

Model README

---

license: apache-2.0

library_name: gguf

tags:

  • gguf
  • llama.cpp
  • text-generation
  • conversational
  • code
  • programming
  • computer-science
  • qwen3

base_model: Qwen/Qwen3-4B

---

Qwen3-4B-Computer-Science-GGUF

GGUF release of Qwen3-4B-Computer-Science, a specialized language model fine-tuned for computer science, software engineering, Python programming, debugging, code generation, and technical reasoning.

This repository provides multiple GGUF quantizations for use with llama.cpp, LM Studio, Ollama, Jan, KoboldCpp, and other GGUF-compatible inference engines.

---

Model Overview

  • Base Model: Qwen/Qwen3-4B
  • Architecture: Qwen3
  • Format: GGUF
  • License: Apache-2.0
  • Language: English
  • Domain: Computer Science & Software Engineering

The model is designed to provide strong performance across software engineering tasks while remaining efficient enough to run locally on modern CPUs and GPUs.

---

Training Data

This model was fine-tuned using openly licensed datasets:

| Dataset | License |

|---------|---------|

| HuggingFaceTB/smoltalk (smol-magpie-ultra) | Apache-2.0 |

| agentica-org/DeepCoder-Preview-Dataset (primeintellect) | MIT |

Training split:

  • 60,989 samples

Evaluation split:

  • 512 samples

---

Available Quantizations

| File | Recommended Use |

|------|-----------------|

| BF16.gguf | Highest quality, requires significant memory |

| Q8_0.gguf | Near-BF16 quality |

| Q6_K.gguf | Excellent quality/performance balance |

| Q5_K_M.gguf | Recommended for most users |

| Q4_K_M.gguf | Best memory efficiency |

---

Recommended Quantization

For most systems:

Q5_K_M offers the best balance between:

  • Quality
  • Memory usage
  • Speed

If memory is limited, use Q4_K_M.

If maximum quality is desired, use Q8_0 or BF16.

---

Example (llama.cpp)

./llama-cli \
  -m Qwen3-4B-Computer-Science-Q5_K_M.gguf \
  -c 8192

---

Example (LM Studio)

  1. Download one of the GGUF files.
  2. Import the model into LM Studio.
  3. Select the model.
  4. Start chatting.

---

Example (Ollama)

Create a Modelfile:

FROM Qwen3-4B-Computer-Science-Q5_K_M.gguf

Then run:

ollama create qwen3-cs -f Modelfile
ollama run qwen3-cs

---

Intended Use

This model is intended for:

  • Software Engineering
  • Python Programming
  • Debugging
  • Code Review
  • Code Generation
  • Technical Question Answering
  • Algorithm Design
  • Computer Science Education

---

Limitations

This model is specialized for computer science tasks.

Performance outside software engineering domains may differ from the original base model.

As with all language models:

  • outputs may contain mistakes
  • generated code should be reviewed
  • security-critical code should always be validated

---

Integrity

SHA-256 hashes for every GGUF file are included in:

SHA256SUMS

Users are encouraged to verify downloaded files before use.

---

License

This repository is released under the Apache-2.0 License.

The fine-tuning datasets are compatible with commercial use:

  • Apache-2.0
  • MIT

---

Acknowledgements

  • Alibaba Qwen Team
  • Hugging Face
  • HuggingFaceTB
  • Agentica
  • llama.cpp contributors

---

Citation

If you use this model in your work, please cite this repository.

@misc{qwen3_4b_computer_science_gguf,
  title={Qwen3-4B-Computer-Science-GGUF},
  author={Irfanuruchi},
  year={2026},
  publisher={Hugging Face}
}

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